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DATAMINE
2010
133views more  DATAMINE 2010»
13 years 7 months ago
Using background knowledge to rank itemsets
Assessing the quality of discovered results is an important open problem in data mining. Such assessment is particularly vital when mining itemsets, since commonly many of the disc...
Nikolaj Tatti, Michael Mampaey
ACL
2006
13 years 9 months ago
Reranking and Self-Training for Parser Adaptation
Statistical parsers trained and tested on the Penn Wall Street Journal (WSJ) treebank have shown vast improvements over the last 10 years. Much of this improvement, however, is ba...
David McClosky, Eugene Charniak, Mark Johnson
BMCBI
2005
152views more  BMCBI 2005»
13 years 7 months ago
Improved profile HMM performance by assessment of critical algorithmic features in SAM and HMMER
Background: Profile hidden Markov model (HMM) techniques are among the most powerful methods for protein homology detection. Yet, the critical features for successful modelling ar...
Markus Wistrand, Erik L. L. Sonnhammer
FPGA
2008
ACM
146views FPGA» more  FPGA 2008»
13 years 9 months ago
FPGA-optimised high-quality uniform random number generators
This paper introduces a method of constructing random number generators from four of the basic primitives provided by FPGAs: Flip-Flips, Lookup-Tables, Shift Registers, and RAMs. ...
David B. Thomas, Wayne Luk
ICANNGA
2007
Springer
149views Algorithms» more  ICANNGA 2007»
14 years 1 months ago
Using Real-Valued Meta Classifiers to Integrate and Contextualize Binding Site Predictions
Currently the best algorithms for transcription factor binding site predictions are severely limited in accuracy. However, a non-linear combination of these algorithms could improv...
Mark Robinson, Offer Sharabi, Yi Sun, Rod Adams, R...